Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
STUDY DESIGN: Retrospective cohort. OBJECTIVE: To evaluate for the presence and magnitude of the "July effect" within elective spine surgery. SUMMARY OF BACKGROUND DATA: The July effect is the hypothetical increase in morbidity and mortality thought to be associated with the influx of new (or newly promoted) trainees during the first portion of the academic year. Studies evaluating for the presence and magnitude of the July effect have demonstrated conflicting results. METHODS: We accessed the American College of Surgeons National Surgical Quality Improvement Program database from 2005-2010. Statistical analyses were conducted using bivariate and multivariate logistic regression. RESULTS: A total of 14,986 cases met inclusion criteria and constitute the study population. Of these, 26.5% occurred in the first academic quarter and 25.3% had resident involvement. The rate of serious adverse events was 1.9 times higher and the rate of any adverse events was 1.6 times higher among cases with resident involvement than among those without (P < 0.001 for both). Among cases without resident involvement, the rates of serious adverse events and any adverse events did not differ by academic quarter. Similarly, among cases with resident involvement, the rates of serious adverse events and any adverse events did not differ by academic quarter. CONCLUSION: We could not demonstrate that the training of new (or newly promoted) residents is associated with an increase in the adverse events of spine surgery. Safeguards that have been put in place to ensure patient safety during this training period seem to be effective. Although adverse events were more common among cases with resident involvement than among cases without resident involvement, our data suggest that this association is more likely a product of the riskier population of cases in which residents participate than of the resident involvement itself.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it